Good with detail? Turn it into flexible remote work AI learns to read documents from examples that people label by hand. Every form, every field, every checkbox a model gets right in the real world traces back to someone who marked it correctly first.
TFH - Face Deduplication Collection
Remote (Global)
May 14, 2026
Job description
The objective of this project is to collect a large and diverse dataset of current neutral selfies, head-pose captures, and historical facial images to support machine-learning research and facial recognition model training at TELUS.
The focus is on capturing real-world variation across lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness. The collection includes:
• Current Neutral Selfies – clean frontal selfies serving as high-quality identity references, with natural variation in appearance and surroundings.
• Current Head-Pose Captures – selfies captured in assigned head directions to introduce pose variation.
• Historical Images – older photos from participants’ galleries to capture natural aging and long-term appearance changes.
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